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Agent Skill · 研究检索

rigorous-reasoning(严谨的推理)

rigorous-reasoning 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

rigorous-reasoning 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 68,654。

总安装 225周安装 9GitHub Stars 9下载 73核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:rigorous-reasoning(严谨的推理)
来源仓库:https://github.com/toilahuongg/shopify-agents-kit
仓库路径:skills/rigorous-reasoning
安装命令:
npx skills add https://github.com/toilahuongg/shopify-agents-kit --skill rigorous-reasoning
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/toilahuongg/shopify-agents-kit --skill rigorous-reasoning

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息。适合根据关键词或任务场景快速定位候选结果。可结合来源仓库和原始 README 核验具体用法。安装命令:npx skills add https://github.com/toilahuongg/shopify-agents-kit --skill rigorous-reasoning。

安装前建议确认权限范围、是否会触发联网或文件读写。

来源仓库内路径:skills/rigorous-reasoning

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/toilahuongg/shopify-agents-kit --skill rigorou…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

rigorous-reasoning 怎么安装?

在终端执行 npx skills add https://github.com/toilahuongg/shopify-agents-kit --skill rigorous-reasonin…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

rigorous-reasoning 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

rigorous-reasoning 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

rigorous-reasoning 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

rigorous-reasoning 用的人多吗?

公开数据是累计安装 225 次,近一周安装 9 次,下载 73 次,GitHub 9 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

rigorous-reasoning 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
rigorous-reasoning

严谨的推理 · 本页

2259只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Rigorous Reasoning

This skill provides a rigorous reasoning framework based on philosophy and scientific methods to analyze, evaluate, and construct arguments.

Core Principles

1. Socratic Method

Ask continuous questions to clarify and challenge assumptions:

Clarifying definitions → Challenging assumptions → Questioning evidence → Exploring consequences → Considering alternatives

Application:

  • "When you say X, how do you define X?"
  • "What assumptions underlie this argument?"
  • "What evidence supports this conclusion?"
  • "If this is true, what are the logical consequences?"

2. Standard Argument Structure

Every argument must have:

PREMISES
  ├── Premise 1: [Verifiable claim]
  ├── Premise 2: [Verifiable claim]
  └── ...
           ↓
INFERENCE RULE
  └── [Modus ponens / Modus tollens / Syllogism / ...]
           ↓
CONCLUSION
  └── [Claim logically derived from premises]

3. Valid Inference Rules

RuleFormExample
Modus PonensP → Q, P ⊢ QIf it rains, the road is wet. It rains. → The road is wet.
Modus TollensP → Q, ¬Q ⊢ ¬PIf it rains, the road is wet. The road is not wet. → It's not raining.
Syllogism∀x(P(x)→Q(x)), P(a) ⊢ Q(a)All men are mortal. Socrates is a man. → Socrates is mortal.
Disjunctive SyllogismP ∨ Q, ¬P ⊢ QEither A or B. Not A. → B.
Hypothetical SyllogismP → Q, Q → R ⊢ P → RIf A then B. If B then C. → If A then C.

Identifying Logical Fallacies

Formal Fallacies

FallacyDescriptionInvalid Example
Affirming the ConsequentP→Q, Q ⊢ P (INVALID)If rain, then wet. Wet → Rain (INVALID: could be other causes)
Denying the AntecedentP→Q, ¬P ⊢ ¬Q (INVALID)If study hard, then pass. Don't study hard → Don't pass (INVALID)

Informal Fallacies

FallacyDescriptionHow to Identify
Ad HominemAttacking the person instead of the argument"He's wrong because he's X"
Straw ManDistorting opponent's argumentCompare with original argument
Appeal to AuthorityCiting irrelevant authorityIs the expert qualified in this field?
False DichotomyPresenting only 2 options when more existIs there a third option?
Slippery SlopeUnproven chain of consequencesIs each step evidenced?
Circular ReasoningConclusion embedded in premisesAre premises independent?
Post HocConfusing correlation with causationIs there a causal mechanism?
Hasty GeneralizationConcluding from small sampleIs the sample representative?
Appeal to EmotionUsing emotion instead of logicSeparate emotion from argument
Tu Quoque"You do it too"Irrelevant to correctness

Scientific Method in Reasoning

Claim Evaluation Process

1. OBSERVATION
   └── What claim needs evaluation?

2. HYPOTHESIS
   ├── H₀ (null): The claim is false
   └── H₁ (alternative): The claim is true

3. PREDICTION
   └── If H₁ is true, what do we expect to observe?

4. TESTING
   ├── Evidence supporting H₁?
   ├── Evidence refuting H₁?
   └── Is the evidence falsifiable?

5. CONCLUSION
   ├── Confidence level?
   └── Alternative hypotheses?

Evidence Standards

Evidence hierarchy (strongest to weakest):

  1. Meta-analysis / Systematic review - Synthesis of multiple studies
  2. Randomized Controlled Trial (RCT) - Controlled experiments
  3. Cohort study - Group follow-up research
  4. Case-control study - Comparative case research
  5. Expert opinion - Professional judgments
  6. Anecdotal evidence - Personal stories (WEAKEST)

Occam's Razor

Among equivalent explanations, choose the simplest one.

Application:

  • Don't multiply entities beyond necessity
  • Prefer hypotheses with fewer assumptions
  • Simple ≠ Correct, but it's a good starting point

Falsifiability Principle (Karl Popper)

A scientific claim must be capable of being refuted.

Test:

  • "What evidence would prove this wrong?"
  • If no answer → Not a scientific claim

Argument Analysis Process

Step 1: Reconstruction

Input: Raw argument
   ↓
1. Identify main conclusion
2. List explicit premises
3. Identify hidden premises
4. Arrange in logical structure
   ↓
Output: Standardized argument

Step 2: Evaluate Premises

For each premise, ask:

  • True? (Is there supporting evidence?)
  • Relevant? (Does it connect to the conclusion?)
  • Sufficient? (Is it strong enough to infer the conclusion?)

Step 3: Evaluate Inference

  • Does the inference follow valid rules?
  • Are there any formal fallacies?
  • Does the conclusion follow from the premises?

Step 4: Consider Counterarguments

  • Are there counterexamples?
  • Are there stronger opposing arguments?
  • Is there additional information that changes the conclusion?

Thinking Tools

Steel Man (Opposite of Straw Man)

Before critiquing, build the strongest version of the opposing argument:

  1. Fully understand the opponent's position
  2. Add reasonable premises they may have omitted
  3. Rephrase in the most compelling way
  4. Then critique

Principle of Charity

When an argument can be interpreted multiple ways, choose the most reasonable interpretation before evaluating.

Reductio ad Absurdum

Prove something false by:

  1. Assume it's true
  2. Derive logical consequences
  3. Show consequences lead to contradiction
  4. Conclude: The initial assumption is false

Thought Experiment

Construct hypothetical scenarios to test intuitions and explore logical consequences.

Quick Evaluation Checklist

When encountering an argument, check:

  • Is the conclusion clearly stated?
  • Are all premises listed?
  • Do premises have supporting evidence?
  • Does inference follow valid rules?
  • No formal fallacies?
  • No informal fallacies?
  • Considered opposing viewpoints?
  • Is the claim falsifiable?
  • Is evidence strong enough?
  • Applied Occam's Razor?

Applied Example

Analyzing an Argument

Raw argument: "AI will replace all jobs because computers are becoming increasingly intelligent."

Reconstruction:

P1: Computers are becoming increasingly intelligent
P2: [Hidden] All jobs can be performed by sufficiently intelligent machines
P3: [Hidden] This development will continue without limits
─────────────────────────────────
C: AI will replace all jobs

Evaluation:

  • P1: Partially true, need to quantify "intelligent"
  • P2: Unproven assumption - are there jobs requiring human elements?
  • P3: Assumption about the future - are there physical/technical limits?
  • Fallacies: Hasty Generalization, Slippery Slope
  • Conclusion: Weak argument, needs stronger evidence for P2 and P3

References

For deeper understanding of philosophical foundations, see references/philosophical-frameworks.md - including:

  • Classical Logic (Aristotle)
  • Rationalism (Descartes, Spinoza, Leibniz)
  • Empiricism (Locke, Hume)
  • Critical Philosophy (Kant)
  • Logical Positivism (Vienna Circle)
  • Philosophy of Science (Karl Popper)
  • Dialectical Method (Hegel, Marx)
  • Pragmatism (Peirce, James, Dewey)

平台分布

Codex

34.95%
按下载量换算26

Claude

32.18%
按下载量换算23

Cursor

18.69%
按下载量换算14

Gemini CLI

10.42%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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